Lilly_Yue

Lilly Yue

Lilly Yue

US government statistician

Lilly Qinli Yue is a US government statististician, known for her work on "real-world evidence" on health care from non-clinical sources such as billing data and product registries.[1] She is deputy director of the Division of Biostatistics in the Center for Devices and Radiological Health of the Food and Drug Administration.[2]

Education and career

Yue has a bachelor's degree in mathematics, a master's degree in stochastic operations research, and a master's degree in mathematical statistics.[2][3] She completed a Ph.D. at Texas A&M University in 1996, with the dissertation Chemometric Calibration and Partial Least Squares supervised by Michael Longnecker.[4]

She was a senior statistician at Eli Lilly and Company before moving to the Food and Drug Administration in 1998.[3]

Recognition

Yue was elected as a Fellow of the American Statistical Association in 2014.[5] In 2020, as part of the RWE Methods Group at the FDA, she was a recipient of the FDA's Excellence in Data Science Group Award, "for extraordinary achievements in the timely development and active promotion of novel statistical methods for leveraging real-world evidence to support regulatory decision-making".[6]

References

  1. [1]
    Sherman, Rachel E.; Anderson, Steven A.; Pan, Gerald J. Dal; Gray, Gerry W.; Gross, Thomas; Hunter, Nina L.; LaVange, Lisa; Marinac-Dabic, Danica; Marks, Peter W.; Robb, Melissa A.; Shuren, Jeffrey; Temple, Robert; Woodcock, Janet; Yue, Lilly Q.; Califf, Robert M. (December 2016), "Real-World Evidence – What Is It and What Can It Tell Us?", New England Journal of Medicine, 375 (23): 2293–2297, doi:10.1056/nejmsb1609216
  2. [2]
    Dr Lilly Yue joins the Editorial Team of Pharmaceutical Statistics in 2021 (PDF), Wiley, retrieved 2023-09-06
  3. [3]
    "Candidates for Directors of ICSA Board (2015–2017): 9. YUE, Lilly" (PDF), International Chinese Statistical Association Bulletin, 26 (2): 82, July 2014, retrieved 2023-09-06
  4. [4]
    Academic program review: Department of Statistics at Texas A&M University (PDF), Texas A&M University, 2022, p. 295, retrieved 2023-09-06
  5. [5]
    ASA Fellows, American Statistical Association, retrieved 2023-09-06
  6. [6]
    Excellence in Data Science Group Award 2009–Present, Food and Drug Administration, retrieved 2023-09-06
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